using 
CSV,
Dates,
DataFrames,
Markdown,
Plots,
Statistics,
StatsPlots
gr()
;

death_path = "COVID-19/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_deaths_global.csv"
confirmed_path = "COVID-19/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv"
;

death = CSV.read(death_path) |> DataFrame! |> x -> rename!(x, Dict(Symbol("Province/State") => :state, Symbol("Country/Region") => :country))
confirmed = CSV.read(confirmed_path) |> DataFrame! |> x -> rename!(x, Dict(Symbol("Province/State") => :state, Symbol("Country/Region") => :country))
;

"""
    convert an array of columns and column names into a markdown table

    parameters: 
        cols : Array[Array[Any]] | DataFrame
            an array of arrays which are the columns of the table
        names : Array[String]
            an array of column names. If inputting a df, input `string.(names(df))`
        df : Boolean
            whether or not the cols are an array of arrays or a dataframe

    returns: String
        string of markdown text
"""
function markdown_table(cols, names; df=false)
    if df
        cols = [col for col in eachcol(cols)]
    end
    output_string = ""
    cols = [repr.(col) for col in cols]
    for i in 1:length(names)
        output_string = output_string * "|" * names[i]
    end
    output_string *= "\n"
    for i in 1:length(names)
        output_string = output_string * "|" * "---"
    end
    output_string *= "\n"
    for row in 1:length(cols[1])
        for col in 1:length(cols)
            output_string = output_string * "|" * cols[col][row]
        end
        output_string *= "\n"
    end
    # displaying strings without quotes
    output_string =  replace(output_string, "\"" => "")

    return output_string
end
;

function country_data(country; state=false, start_date=Dates.Date(2020, 1, 22), end_date="max")
    aggregate(x) = [sum(col) for col in eachcol(x)]
    
    state_mask = typeof(state) == String ? death.state .== state : true
    d = death[(death.country .== country) .& state_mask, 5:end] |> aggregate
    dates = [Dates.Date(2020, 1, 22) + Dates.Day(day) for day in 1:length(d)] |> x -> reshape(x, :, 1)
    state_mask = typeof(state) == String ? confirmed.state .== state : true
    c = confirmed[(confirmed.country .== country) .& state_mask, 5:end] |> aggregate
    
    df = convert(DataFrame, dates) |> x -> rename!(x, [:date])
    country_name = typeof(state) == String ? country * "-" * state : country
    df[!, :country] .= country_name
    df[!, :confirmed] = c
    df[!, :deaths] = d
    df[!, :death_rate] = d ./ c
    df[!, :new_cases] .= 0
    df[2:end, :new_cases] = df[2:end, :confirmed] .- df[1:end-1, :confirmed]
    df[!, :new_deaths] .= 0
    df[2:end, :new_deaths] = df[2:end, :deaths] .- df[1:end-1, :deaths]
    df[!, :acceleration_cases] .= 0
    df[2:end, :acceleration_cases] = df[2:end, :new_cases] .- df[1:end-1, :new_cases]
    df[!, :acceleration_deaths] .= 0
    df[2:end, :acceleration_deaths] = df[2:end, :new_deaths] .- df[1:end-1, :new_deaths]
    df[!, :days_since_100] .= 0
    counter = 0
    for row in eachrow(df)
        if row.confirmed > 100
            counter += 1
        end
        row.days_since_100 = counter
    end
    df[!, :days_since_10] .= 0
    counter = 0
    for row in eachrow(df)
        if row.deaths > 10
            counter += 1
        end
        row.days_since_10 = counter
    end
    
    if end_date == "max"
        end_date = maximum(df.date)
    end
    return df[(df.date .>= start_date) .& (df.date .<= end_date), :]
end
;

function plot_country(country; state=false, metric=:confirmed, start_date=Dates.Date(2020, 1, 22), end_date="max", days_since_100=false)
    data = country_data(country; state=state, start_date=start_date, end_date=end_date)
    if days_since_100
        if metric == :confirmed
            plot(data[data.days_since_100 .> 0, :days_since_100], data[data.days_since_100 .> 0, metric], label=country, legend=:outertopright, size=(1000, 500))
        else
            plot(data[data.days_since_10 .> 0, :days_since_10], data[data.days_since_10 .> 0, metric], label=country, legend=:outertopright, size=(1000, 500))
        end
    else
        plot(data.date, data[!, metric], label=country, legend=:outertopright, size=(1000, 500))
    end
    
    plot!([0], linetype=:hline, color=:black, label="")
    plot!(yformatter=:plain)
end
function plot_country!(country; state=false, metric=:confirmed, start_date=Dates.Date(2020, 1, 22), end_date="max", days_since_100=false)
    data = country_data(country; state=state, start_date=start_date, end_date=end_date)
    if days_since_100
        if metric == :confirmed
            plot!(data[data.days_since_100 .> 0, :days_since_100], data[data.days_since_100 .> 0, metric], label=country, legend=:outertopright, size=(1000, 500))
        else
            plot!(data[data.days_since_10 .> 0, :days_since_10], data[data.days_since_10 .> 0, metric], label=country, legend=:outertopright, size=(1000, 500))
        end
    else
        plot!(data.date, data[!, metric], label=country, legend=:outertopright, size=(1000, 500))
    end
    plot!(yformatter=:plain)
end
bar_plot(country, metric) = bar(
    all_country_data[
        (all_country_data.country .== country) .& (all_country_data.date .>= Dates.Date(2020, 1, 1)),
        :date
    ], 
    all_country_data[
        (all_country_data.country .== country) .& (all_country_data.date .>= Dates.Date(2020, 1, 1)),
        metric
    ], 
    legend=false, 
    linecolor=1, 
    title=country,
    yformatter=:plain
)
function accel_plot(country_name="World")
    if country_name == "World"
        tmp = all_country_data
    else
        tmp = all_country_data[all_country_data.country .== country_name, :]
    end
    agg = by(tmp, [:date], :confirmed => sum, :deaths => sum)
    conf = plot(agg.date, agg.confirmed_sum, legend=false, title="$country_name Confirmed Cases", size=(1400, 700), color=:grey, yformatter=:plain)
    death_plot = plot(agg.date, agg.deaths_sum, legend=false, title="$country_name Deaths", size=(1400, 700), color=:orange, yformatter=:plain)

    # derivates
    agg[!, :new_cases] .= 0
    agg[!, :new_cases][2:end] = agg.confirmed_sum[2:end] - agg.confirmed_sum[1:end-1]
    agg[!, :new_deaths] .= 0
    agg[!, :new_deaths][2:end] = agg.deaths_sum[2:end] - agg.deaths_sum[1:end-1]
    agg[!, :conf_acceleration] .= 0
    agg[!, :conf_acceleration][2:end] = agg.new_cases[2:end] - agg.new_cases[1:end-1]
    agg[!, :death_acceleration] .= 0
    agg[!, :death_acceleration][2:end] = agg.new_deaths[2:end] - agg.new_deaths[1:end-1]

    # moving average
    moving_average(vs,n) = [sum(@view vs[i:(i+n-1)])/n for i in 1:(length(vs)-(n-1))]
    n_days = 3
    ma_date = agg.date[1 + n_days-1:end]
    conf_slope = moving_average(agg.new_cases, n_days)
    death_slope = moving_average(agg.new_deaths, n_days)
    conf_acc = moving_average(agg.conf_acceleration, n_days)
    death_acc = moving_average(agg.death_acceleration, n_days)

    p_conf_slope = plot(ma_date, conf_slope, legend=false, title="$country_name 1st Derivative (new cases)", size=(1400, 700), color=:grey)
    plot!([0], linetype=:hline, color=:black, label="", yformatter=:plain)

    p_death_slope = plot(ma_date, death_slope, legend=false, title="$country_name 1st Derivative (new deaths)", size=(1400, 700), color=:orange)
    plot!([0], linetype=:hline, color=:black, label="", yformatter=:plain)

    p_conf_acc = plot(ma_date, conf_acc, legend=false, title="$country_name 2nd Derivative (cases acceleration)", size=(1400, 700), color=:grey)
    plot!([0], linetype=:hline, color=:black, label="", yformatter=:plain)

    p_death_acc = plot(ma_date, death_acc, legend=false, title="$country_name 2nd Derivative (deaths acceleration)", size=(1400, 700), color=:orange)
    plot!([0], linetype=:hline, color=:black, label="", yformatter=:plain)

    plot(conf, death_plot, p_conf_slope, p_death_slope, p_conf_acc, p_death_acc, layout=(3,2))
end
;

all_countries = death.country |> unique |> sort
all_country_data = vcat([country_data(country) for country in all_countries]...)
current_state = by(all_country_data, [:country], :confirmed => maximum, :deaths => maximum)
current_state[!, :death_rate] = current_state.deaths_maximum ./ current_state.confirmed_maximum
;

Markdown.parse("""
    # Overview of COVID-19 as of $(maximum(all_country_data.date))
    This page uses data from https://github.com/CSSEGISandData/COVID-19 (Johns Hopkins CSSE is the original source) to create a report on the status of COVID-19 cases and deaths around the world. It is updated once a day around 10:00am CET.
    """)

Worldwide Current State¶

tmp = current_state
Markdown.parse("""
- Confirmed cases: $(sum(tmp.confirmed_maximum))
- Deaths: $(sum(tmp.deaths_maximum))
- Death Rate: $(round(sum(tmp.deaths_maximum) / sum(tmp.confirmed_maximum) * 100, digits=2))%
""")

accel_plot("World")
plot!(size=(900, 700))

Top 10 Worst Affected Countries¶

Confirmed¶

top_10 = sort(current_state, order(:confirmed_maximum, rev=true))[1:10, :]
top_10[!, :death_rate] = string.(round.(top_10.death_rate * 100, digits=2)) .* "%"
Markdown.parse(
    markdown_table(top_10, ["Country", "Confirmed Cases", "Deaths", "Death Rate"]; df=true)
)

Acceleration (>1000 cases now)¶

The Acceleration of Last 5 Days column is calculated by the average second derivative over the last 5 days / number of cases 5 days ago. It doesn't have much intrinsic meaning but is rather a more comparable/relative measure between countries of how fast new cases are accelerating.

countries = unique(all_country_data.country)
acceleration = []
cases_5_ago = []
cases_now = []
for country in countries
    metric = mean(all_country_data[all_country_data.country .== country, :acceleration_cases][end-4:end])
    metric /= all_country_data[all_country_data.country .== country, :confirmed][end-4]
    if isnan(metric)
        metric = 0
    end
    push!(acceleration, metric)
    push!(cases_5_ago, all_country_data[all_country_data.country .== country, :confirmed][end-4])
    push!(cases_now, all_country_data[all_country_data.country .== country, :confirmed][end])
end
last_5 = rename!(DataFrame([countries, acceleration, cases_now, cases_5_ago]), [:country, :last_5_accel, :cases_now, :cases_5_ago])
last_5[!, :perc_increase] = last_5.cases_now ./ last_5.cases_5_ago .- 1
tmp = sort(last_5[(last_5.cases_5_ago .> 20) .& (last_5.cases_now .> 1000), :], order(:last_5_accel, rev=true))
tmp[!, :perc_increase] = string.(round.(tmp.perc_increase .* 100, digits=2)) .* "%"
rename!(tmp, [:Country, Symbol("Acceleration of Last 5 Days"), Symbol("Cases Now"), Symbol("Cases 5 Days Ago"), Symbol("% Increase in 5 Days")])
tmp[!, Symbol("Acceleration of Last 5 Days")] = string.(round.(tmp[!, Symbol("Acceleration of Last 5 Days")] * 100, digits=2)) .* "%"

Markdown.parse(
    markdown_table(tmp, string.(names(tmp)), df=true)
)

function individual_country(country; comparison_country="Italy")
    # line plots
    cases_100 = plot_country(country, days_since_100=true, metric=:confirmed)
    plot_country!(comparison_country, days_since_100=true, metric=:confirmed)
    plot!(title="$country Days Since 100th Case", titlefont=font(10))
    deaths_10 = plot_country(country, days_since_100=true, metric=:deaths)
    plot_country!(comparison_country, days_since_100=true, metric=:deaths)
    plot!(title="$country Days Since 10th Death", titlefont=font(10))
    line_plots = plot(cases_100, deaths_10, layout=(2,1))
    
    #accel plots
    accel_plots = accel_plot(country)
    plot!(titlefont=font(10))
    
    # bar plots
    cases_bar = bar_plot(country, :new_cases)
    plot!(title="$country New Cases Per Day", titlefont=font(10))
    deaths_bar = bar_plot(country, :new_deaths)
    plot!(title="$country Deaths Per Day", titlefont=font(10))
    bar_plots = plot(cases_bar, deaths_bar, layout=(2,1))
    
    final_plot = plot(accel_plots, line_plots, bar_plots, layout=(3, 1))
    plot!(size=(900, 1400))
    return final_plot
end
;

Countries¶

Days since 100th case and 10th death plotted with Italy for comparison. Only countries with >= 500 confirmed cases show graphs. Derivative plots are 3 days moving average.

for coun in all_countries
    data = country_data(coun)
    display(Markdown.parse("## $coun"))
    Markdown.parse("""
- Confirmed cases: $(maximum(data.confirmed))
- Deaths: $(maximum(data.deaths))
- Death Rate: $(round(maximum(data.deaths) / maximum(data.confirmed) * 100, digits=2))%
""") |> display
    if maximum(data.confirmed) >= 500 || coun == "Hungary"
        display(individual_country(coun))
    end
end

Country	Confirmed Cases	Deaths	Death Rate
US	140886	2467	1.75%
Italy	97689	10779	11.03%
China	82122	3304	4.02%
Spain	80110	6803	8.49%
Germany	62095	533	0.86%
France	40708	2611	6.41%
Iran	38309	2640	6.89%
United Kingdom	19780	1231	6.22%
Switzerland	14829	300	2.02%
Netherlands	10930	772	7.06%

Country	Acceleration of Last 5 Days	Cases Now	Cases 5 Days Ago	% Increase in 5 Days
Turkey	12.1%	9217	2433	278.83%
Philippines	7.96%	1418	636	122.96%
Russia	6.47%	1534	658	133.13%
Belgium	4.76%	10836	4937	119.49%
Israel	3.89%	4247	2369	79.27%
Portugal	3.27%	5962	2995	99.07%
Romania	3.2%	1815	906	100.33%
US	2.89%	140886	65778	114.18%
United Kingdom	2.14%	19780	9640	105.19%
Japan	1.65%	1866	1307	42.77%
Poland	1.37%	1862	1051	77.16%
Greece	1.14%	1156	821	40.8%
Chile	0.95%	2139	1142	87.3%
Netherlands	0.92%	10930	6438	69.77%
Spain	0.86%	80110	49515	61.79%
Iran	0.84%	38309	27017	41.8%
Thailand	0.79%	1388	934	48.61%
Indonesia	0.58%	1285	790	62.66%
Denmark	0.56%	2564	1862	37.7%
Malaysia	0.49%	2470	1796	37.53%
Czechia	0.34%	2817	1654	70.31%
Germany	0.25%	62095	37323	66.37%
Brazil	0.23%	4256	2554	66.64%
Norway	0.18%	4284	3084	38.91%
Sweden	0.1%	3700	2526	46.48%
Pakistan	0.09%	1597	1063	50.24%
France	0.08%	40708	25600	59.02%
Korea, South	0.06%	9583	9137	4.88%
Canada	0.01%	6280	3251	93.17%
China	0.01%	82122	81661	0.56%
Ecuador	0.0%	1924	1173	64.02%
India	0.0%	1024	657	55.86%
Italy	-0.01%	97689	74386	31.33%
Ireland	-0.05%	2615	1564	67.2%
Iceland	-0.08%	1020	737	38.4%
Australia	-0.15%	3984	2364	68.53%
Finland	-0.43%	1240	880	40.91%
Switzerland	-0.6%	14829	10897	36.08%
Austria	-1.05%	8788	5588	57.27%
Luxembourg	-1.58%	1950	1333	46.29%
South Africa	-1.66%	1280	709	80.54%
Saudi Arabia	-2.42%	1299	900	44.33%

Overview of COVID-19 as of 2020-03-30¶

Worldwide Current State¶

Top 10 Worst Affected Countries¶

Confirmed¶

Acceleration (>1000 cases now)¶

Countries¶

Afghanistan¶

Albania¶

Algeria¶

Andorra¶

Angola¶

Antigua and Barbuda¶

Argentina¶

Armenia¶

Australia¶

Austria¶

Azerbaijan¶

Bahamas¶

Bahrain¶

Bangladesh¶

Barbados¶

Belarus¶

Belgium¶

Belize¶

Benin¶

Bhutan¶

Bolivia¶

Bosnia and Herzegovina¶

Brazil¶

Brunei¶

Bulgaria¶

Burkina Faso¶

Burma¶

Cabo Verde¶

Cambodia¶

Cameroon¶

Canada¶

Central African Republic¶

Chad¶

Chile¶

China¶

Colombia¶

Congo (Brazzaville)¶

Congo (Kinshasa)¶

Costa Rica¶

Cote d'Ivoire¶

Croatia¶

Cuba¶

Cyprus¶

Czechia¶

Denmark¶

Diamond Princess¶

Djibouti¶

Dominica¶

Dominican Republic¶

Ecuador¶

Egypt¶

El Salvador¶

Equatorial Guinea¶

Eritrea¶

Estonia¶

Eswatini¶

Ethiopia¶

Fiji¶

Finland¶

France¶

Gabon¶

Gambia¶

Georgia¶

Germany¶

Ghana¶

Greece¶

Grenada¶

Guatemala¶

Guinea¶

Guinea-Bissau¶

Guyana¶

Haiti¶

Holy See¶

Honduras¶